About this trial
TIER-PC is an adaptive model of delivering palliative care that provides the right level of care to the right patients at the right time. It represents an adaption of the Mount Sinai PALLIATIVE CARE AT HOME (PC@H) program, which delivers home-based palliative care. TIER-PC increases the number and intensity of disciplines added to the patient's care team as their symptoms worsen and function declines. In Tier 1, patients who are able to care for themselves and no/mild symptoms receive a community health worker (CHW) trained to elicit illness understanding in a culturally competent way. In Tier 2, for patients with poorer function and mild symptoms, a social worker (SW), trained in serious illness communication, joins the CHW to further elicit patients' goals and prognostic understanding while communicating symptom needs to their primary clinician. In Tier 3, as function decreases and symptoms increase, an advance practice nurse (APN) joins the CHW and SW to manage complex symptoms. Finally, in Tier 4, for those older adults with the poorest function and most complex symptoms, a physician joins the team to ensure that the most complex needs (e.g., end-of-life treatment preferences and multifaceted symptom control) are met. The CHW follows patients longitudinally across all tiers and re-allocates them to the appropriate tier based on their evolving needs.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Advanced Heart Failure (HF) with two HF-related hospitalizations within the last 12 months or
Advanced lung or non-colorectal gastrointestinal cancer (pancreatic, gastric, hepatobiliary, small bowel, esophageal) with one hospitalization within the last 6 months
KPS > 50% (ECOG 0, 1 or 2)
> 2 outpatient MSHS visits in prior 12 months
Disqualifiers
Diagnoses of both cancer and advanced HF
Lung cancer with a driver mutation (e.g., EGFR) that confers a favorable prognosis and does not follow typical trajectory
Patients with > 1 visit to Outpatient Supportive Oncology/Cardiology visit
Patients with last visit to Outpatient Supportive Oncology/Cardiology < 3 months ago
Trial design
Parallel
Treatments tested in this trial
Tier-Palliative Care
BehavioralTIER-PC is an adaptive model of delivering palliative care that provides the right level of care to the right patients at the right time. It represents an adaption of the Mount Sinai PALLIATIVE CARE AT HOME (PC@H) program, which delivers home-based palliative care. TIER-PC increases the number and intensity of disciplines added to the patient's care team as their symptoms worsen and function declines.
Treatment groups
Trial outcomes
Primary outcomes
The proportion of screened eligible patients
The proportion of screened eligible patients that are enrolled in the trial.
Secondary outcomes
The proportion of patients completing the final 3-month visit
The proportion of the patients completing the final 3-month visit among all enrolled patients.
Number of TIER-PC intervention visits received per patient per month
The fidelity to intervention is defined as the number of TIER-PC intervention visits received per patient per month in the TIER-PC arm during the follow-up period.
Edmonton Symptom Assessment Scale (ESAS)
Patient symptoms will be measured (e.g., pain, shortness of breath) using the 9-item Edmonton Symptom Assessment Scale (ESAS) validated for serious illness. Each item is 10-point scale, total score ranges 0 (no symptoms) - 90 (worst severity), with higher scores indicating worse symptom severity.
Quality of Life measured using Functional Assessment of Chronic Illness Therapy-Palliative Care Scale (FACIT-Pal)
Quality of life (QoL) using the Functional Assessment of Chronic Illness Therapy-Palliative Care Scale (FACIT-Pal), a 46-item QoL questionnaire validated in patients with advanced disease. Each item is scored on a 5-point Likert scale from 0 (not at all) - 4 (very much). Total score ranges 0-184, with higher scores indicating better quality of life.
Sponsors and contacts
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Icahn School of Medicine at Mount Sinai
Lead sponsor
National Institute of Nursing Research (NINR)
Collaborator